Storm-Time Relative Total Electron Content Modelling Using Machine Learning Techniques

Storm-Time Relative Total Electron Content Modelling Using Machine Learning Techniques

Accurately predicting total electron content (TEC) during geomagnetic storms is still a challenging task for ionospheric models. In this work, a neural-network (NN)-based model is proposed which predicts relative TEC with respect to the preceding 27-day median TEC, during storm time for the European...

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Bibliographic Details
Main Authors: Marjolijn Adolfs, Mohammed Mainul Hoque, Yuri Y. Shprits
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Remote Sensing
Subjects:
ionosphere
relative total electron content
geomagnetic storms
neural networks
NTCM
European storm-time model
Online Access:https://www.mdpi.com/2072-4292/14/23/6155

Internet

https://www.mdpi.com/2072-4292/14/23/6155

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